The dilution effect of healthy lifestyles on the risk of cognitive function attributed to socioeconomic status among Chinese older adults: A national wide prospective cohort study

Background Lower socioeconomic status (SES) is a risk factor for poor cognitive function, while a healthy lifestyle is associated with better cognitive function. We examined the complex relationship between SES and a healthy lifestyle and cognitive function among older Chinese adults. Methods We used a national prospective cohort of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2008–18, aged 65 years and older with normal cognition at baseline. Participants were categorised into the favourable group if they had four to six healthy lifestyle factors and the unfavourable group for zero to three factors. SES was classified as higher and lower by assessing the socioeconomic vulnerability index (SEVI) with six components. Cognitive function was measured using the Mini-Mental State Examination (MMSE) scores and the standardised Z-scores. We applied the linear mixed effects and time-dependent Cox regression models to explore associations and further stratified the analysis by healthy lifestyles. Results A total of 6851 participants were included (the mean age was 80.87, 43.44% had a favourable lifestyle, and 49.29% had higher SES). Over the 10-year follow-up period, SES status and lifestyle profiles significantly affected the decline in the standardised Z-scores (P < 0.05). The higher SES group with favourable lifestyles exhibited a slower cognitive decline than those with lower SES (by 0.031 points per year, P < 0.05). The association was not observed in those in the unfavourable group (0.010 points per year, P > 0.05). During a follow-up, 25.06% of participants developed cognitive impairment (MMSE<18). We also observed a significant interaction between SES and healthy lifestyles (P < 0.05), with the corresponding associations of SES being more pronounced among participants with unfavourable lifestyles (hazard ratio (HR) = 0.821; 95% confidence interval (CI) = 0.701–0.960) than those with favourable lifestyles (HR = 1.006; 95% CI = 0.844–1.200). Conclusions A healthy lifestyle may attenuate the adverse impacts of lower SES on cognitive function among older adults. This study might provide important information for protecting cognitive function, especially in low- and middle-income countries.

Supplementary table 1.The Chinese version of the mini-mental state examination adopted in the CLHLS.

Orientation
What time of day is it right now (morning, afternoon, evening)? 1 What is the animal year of this year? 1 What is the date (day and month) of the mid-autumn festival? 1 What is the season right now? 1 What is the name of this county or district? 1 Please name as many kinds of food as possible in 1 minute (1 point for each food and 7 points for those who name 7 or more foods).
7 Registration The individual is asked to follow the interviewer's instruction: "Take the paper using your right hand (1 point), fold it in the middle using both hands (1 point), and place the paper on the floor (1 point)." 3 Note: We scored each question as zero (wrong or unable to answer) or one (correct) , and the scores ranged between 0 and 30, with a higher score implying better cognitive performance.

table 3 .
Baseline characteristics of two socioeconomic status groups.table 5. Associations of the number of healthy lifestyle factors and SEVI with cognitive decline using Rubin's method.Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Supplementary table 6. Association between SEVI and cognitive decline using Rubin's method, stratified by healthy lifestyle.table7. Association of each lifestyle and SES factor and cognitive decline using Rubin's method.table8. Associations of healthy lifestyle and socioeconomic status with cognitive decline using Rubin's method: subgroup analyses.Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Supplementary table 9. Association between socioeconomic status and cognitive decline using Rubin's method, stratified by healthy lifestyle: subgroup analyses.Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Supplementary table 10.Baseline characteristics of participants by follow-up cognitive impairment.Supplementary table 13 Hazard ratios of socioeconomic status on the onset of cognitive impairment in a population stratified by healthy lifestyle using Rubin's method: subgroup analyses.Adjusted covariates of a time dependent Cox regression model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Adjusted covariates of a time dependent Cox regression model included MMSE score at baseline, age, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.cAdjusted covariates of a time dependent Cox regression model included MMSE score at baseline, age, gender, region, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Supplementary table 14.Association of healthy lifestyle and socioeconomic status with cognitive impairment by adjusting with the death as the competing risk and using the inverse probability weighting method.Adjusted covariates included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.
a Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.bPerformed by treating the number of healthy lifestyle factors as a numeric variable.Supplementary a a Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Supplementary a Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.Supplementary a Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.bAdjusted covariates of linear mixed effect model included MMSE score at baseline, age, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.ca Adjusted covariates of linear mixed effect model included MMSE score at baseline, age, gender, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.bAdjusted covariates of linear mixed effect model included MMSE score at baseline, age, region, marital status, BMI, BADL disability, IADL disability, hypertension, diabetes, heart disease, stroke& cerebrovascular disease, and dyslipidemia.ca b a Model 1 adjusted with the death as the competing risk.b Model 2 using the inverse probability weighting method.c